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gdpr-dsgvo-expertGDPR DSGVO 专家

Agent Skill

gdpr-dsgvo-expert 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

62,497

周安装

2,553

GitHub Stars

3

下载量

20,016
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:gdpr-dsgvo-expert(GDPR DSGVO 专家)
来源仓库:https://github.com/alirezarezvani/gdpr-dsgvo-expert
安装命令:
openclaw skills install gdpr-dsgvo-expert
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install gdpr-dsgvo-expert

简介

gdpr-dsgvo-expert 实现 GDPR 和 DSGVO 合规自动化,降低数据保护违规风险。

  • 扫描代码库中的隐私漏洞,生成 DPIA 报告并跟踪数据主体请求。
  • 提供数据处理协议模板和同意管理机制设计建议。
  • 安装命令:openclaw skills install gdpr-dsgvo-expert,需读取项目配置文件。
  • 处理个人数据时务必启用脱敏模式,禁止导出真实用户信息。

SKILL.md

name
gdpr-dsgvo-expert
description
GDPR and German DSGVO compliance automation. Scans codebases for privacy risks, generates DPIA documentation, tracks data subject rights requests. Use for GDPR compliance assessments, privacy audits, data protection planning, DPIA generation, and data subject rights management.

GDPR/DSGVO Expert

Tools and guidance for EU General Data Protection Regulation (GDPR) and German Bundesdatenschutzgesetz (BDSG) compliance.


Table of Contents

- GDPR Compliance Checker - DPIA Generator - Data Subject Rights Tracker


Tools

GDPR Compliance Checker

Scans codebases for potential GDPR compliance issues including personal data patterns and risky code practices.

# Scan a project directory
python scripts/gdpr_compliance_checker.py /path/to/project

# JSON output for CI/CD integration
python scripts/gdpr_compliance_checker.py . --json --output report.json

Detects:

  • Personal data patterns (email, phone, IP addresses)
  • Special category data (health, biometric, religion)
  • Financial data (credit cards, IBAN)
  • Risky code patterns:

- Logging personal data - Missing consent mechanisms - Indefinite data retention - Unencrypted sensitive data - Disabled deletion functionality

Output:

  • Compliance score (0-100)
  • Risk categorization (critical, high, medium)
  • Prioritized recommendations with GDPR article references

DPIA Generator

Generates Data Protection Impact Assessment documentation following Art. 35 requirements.

# Get input template
python scripts/dpia_generator.py --template > input.json

# Generate DPIA report
python scripts/dpia_generator.py --input input.json --output dpia_report.md

Features:

  • Automatic DPIA threshold assessment
  • Risk identification based on processing characteristics
  • Legal basis requirements documentation
  • Mitigation recommendations
  • Markdown report generation

DPIA Triggers Assessed:

  • Systematic monitoring (Art. 35(3)(c))
  • Large-scale special category data (Art. 35(3)(b))
  • Automated decision-making (Art. 35(3)(a))
  • WP29 high-risk criteria

Data Subject Rights Tracker

Manages data subject rights requests under GDPR Articles 15-22.

# Add new request
python scripts/data_subject_rights_tracker.py add \
  --type access --subject "John Doe" --email "john@example.com"

# List all requests
python scripts/data_subject_rights_tracker.py list

# Update status
python scripts/data_subject_rights_tracker.py status --id DSR-202601-0001 --update verified

# Generate compliance report
python scripts/data_subject_rights_tracker.py report --output compliance.json

# Generate response template
python scripts/data_subject_rights_tracker.py template --id DSR-202601-0001

Supported Rights:

RightArticleDeadline
AccessArt. 1530 days
RectificationArt. 1630 days
ErasureArt. 1730 days
RestrictionArt. 1830 days
PortabilityArt. 2030 days
ObjectionArt. 2130 days
Automated decisionsArt. 2230 days

Features:

  • Deadline tracking with overdue alerts
  • Identity verification workflow
  • Response template generation
  • Compliance reporting

Reference Guides

GDPR Compliance Guide

references/gdpr_compliance_guide.md

Comprehensive implementation guidance covering:

  • Legal bases for processing (Art. 6)
  • Special category requirements (Art. 9)
  • Data subject rights implementation
  • Accountability requirements (Art. 30)
  • International transfers (Chapter V)
  • Breach notification (Art. 33-34)

German BDSG Requirements

references/german_bdsg_requirements.md

German-specific requirements including:

  • DPO appointment threshold (§ 38 BDSG - 20+ employees)
  • Employment data processing (§ 26 BDSG)
  • Video surveillance rules (§ 4 BDSG)
  • Credit scoring requirements (§ 31 BDSG)
  • State data protection laws (Landesdatenschutzgesetze)
  • Works council co-determination rights

DPIA Methodology

references/dpia_methodology.md

Step-by-step DPIA process:

  • Threshold assessment criteria
  • WP29 high-risk indicators
  • Risk assessment methodology
  • Mitigation measure categories
  • DPO and supervisory authority consultation
  • Templates and checklists

Workflows

Workflow 1: New Processing Activity Assessment

Step 1: Run compliance checker on codebase
        → python scripts/gdpr_compliance_checker.py /path/to/code

Step 2: Review findings and compliance score
        → Address critical and high issues

Step 3: Determine if DPIA required
        → Check references/dpia_methodology.md threshold criteria

Step 4: If DPIA required, generate assessment
        → python scripts/dpia_generator.py --template > input.json
        → Fill in processing details
        → python scripts/dpia_generator.py --input input.json --output dpia.md

Step 5: Document in records of processing activities

Workflow 2: Data Subject Request Handling

Step 1: Log request in tracker
        → python scripts/data_subject_rights_tracker.py add --type [type] ...

Step 2: Verify identity (proportionate measures)
        → python scripts/data_subject_rights_tracker.py status --id [ID] --update verified

Step 3: Gather data from systems
        → python scripts/data_subject_rights_tracker.py status --id [ID] --update in_progress

Step 4: Generate response
        → python scripts/data_subject_rights_tracker.py template --id [ID]

Step 5: Send response and complete
        → python scripts/data_subject_rights_tracker.py status --id [ID] --update completed

Step 6: Monitor compliance
        → python scripts/data_subject_rights_tracker.py report

Workflow 3: German BDSG Compliance Check

Step 1: Determine if DPO required
        → 20+ employees processing personal data automatically
        → OR processing requires DPIA
        → OR business involves data transfer/market research

Step 2: If employees involved, review § 26 BDSG
        → Document legal basis for employee data
        → Check works council requirements

Step 3: If video surveillance, comply with § 4 BDSG
        → Install signage
        → Document necessity
        → Limit retention

Step 4: Register DPO with supervisory authority
        → See references/german_bdsg_requirements.md for authority list

Key GDPR Concepts

Legal Bases (Art. 6)

  • Consent: Marketing, newsletters, analytics (must be freely given, specific, informed)
  • Contract: Order fulfillment, service delivery
  • Legal obligation: Tax records, employment law
  • Legitimate interests: Fraud prevention, security (requires balancing test)

Special Category Data (Art. 9)

Requires explicit consent or Art. 9(2) exception:

  • Health data
  • Biometric data
  • Racial/ethnic origin
  • Political opinions
  • Religious beliefs
  • Trade union membership
  • Genetic data
  • Sexual orientation

Data Subject Rights

All rights must be fulfilled within 30 days (extendable to 90 for complex requests):

  • Access: Provide copy of data and processing information
  • Rectification: Correct inaccurate data
  • Erasure: Delete data (with exceptions for legal obligations)
  • Restriction: Limit processing while issues are resolved
  • Portability: Provide data in machine-readable format
  • Object: Stop processing based on legitimate interests

German BDSG Additions

TopicBDSG SectionKey Requirement
DPO threshold§ 3820+ employees = mandatory DPO
Employment§ 26Detailed employee data rules
Video§ 4Signage and proportionality
Scoring§ 31Explainable algorithms

适合场景

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02

用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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